Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development
<italic>Goal:</italic> Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. <italic>Methods:</italic> We tested five s...
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Engineering in Medicine and Biology |
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| Online Access: | https://ieeexplore.ieee.org/document/10414161/ |
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| author | Giles Hamilton-Fletcher Mingxin Liu Diwei Sheng Chen Feng Todd E. Hudson John-Ross Rizzo Kevin C. Chan |
| author_facet | Giles Hamilton-Fletcher Mingxin Liu Diwei Sheng Chen Feng Todd E. Hudson John-Ross Rizzo Kevin C. Chan |
| author_sort | Giles Hamilton-Fletcher |
| collection | DOAJ |
| description | <italic>Goal:</italic> Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. <italic>Methods:</italic> We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1–3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). <italic>Results:</italic> For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2–6.2 cm average error at 2–3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. <italic>Conclusions:</italic> We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV. |
| format | Article |
| id | doaj-art-fd22848451de465eb3d618634439b8fd |
| institution | Kabale University |
| issn | 2644-1276 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
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| series | IEEE Open Journal of Engineering in Medicine and Biology |
| spelling | doaj-art-fd22848451de465eb3d618634439b8fd2025-01-29T00:01:25ZengIEEEIEEE Open Journal of Engineering in Medicine and Biology2644-12762024-01-015545810.1109/OJEMB.2024.335856210414161Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology DevelopmentGiles Hamilton-Fletcher0https://orcid.org/0000-0001-5903-4334Mingxin Liu1https://orcid.org/0009-0004-0101-4102Diwei Sheng2https://orcid.org/0009-0000-0587-4725Chen Feng3https://orcid.org/0000-0003-3211-1576Todd E. Hudson4https://orcid.org/0000-0003-4506-2670John-Ross Rizzo5https://orcid.org/0009-0008-5274-3160Kevin C. Chan6https://orcid.org/0000-0003-4012-7084Department of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, NY, USADepartment of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, NY, USADepartment of Civil and Urban Engineering & Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USADepartment of Civil and Urban Engineering & Department of Mechanical and Aerospace Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USADepartment of Rehabilitative Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, NY, USADepartment of Rehabilitative Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, NY, USADepartment of Ophthalmology, NYU Grossman School of Medicine, NYU Langone Health, New York University, New York, NY, USA<italic>Goal:</italic> Distance information is highly requested in assistive smartphone Apps by people who are blind or low vision (PBLV). However, current techniques have not been evaluated systematically for accuracy and usability. <italic>Methods:</italic> We tested five smartphone-based distance-estimation approaches in the image center and periphery at 1–3 meters, including machine learning (CoreML), infrared grid distortion (IR_self), light detection and ranging (LiDAR_back), and augmented reality room-tracking on the front (ARKit_self) and back-facing cameras (ARKit_back). <italic>Results:</italic> For accuracy in the image center, all approaches had <±2.5 cm average error, except CoreML which had ±5.2–6.2 cm average error at 2–3 meters. In the periphery, all approaches were more inaccurate, with CoreML and IR_self having the highest average errors at ±41 cm and ±32 cm respectively. For usability, CoreML fared favorably with the lowest central processing unit usage, second lowest battery usage, highest field-of-view, and no specialized sensor requirements. <italic>Conclusions:</italic> We provide key information that helps design reliable smartphone-based visual assistive technologies to enhance the functionality of PBLV.https://ieeexplore.ieee.org/document/10414161/Assistive technologysensory substitutionblindnesslow visionnavigation |
| spellingShingle | Giles Hamilton-Fletcher Mingxin Liu Diwei Sheng Chen Feng Todd E. Hudson John-Ross Rizzo Kevin C. Chan Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development IEEE Open Journal of Engineering in Medicine and Biology Assistive technology sensory substitution blindness low vision navigation |
| title | Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development |
| title_full | Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development |
| title_fullStr | Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development |
| title_full_unstemmed | Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development |
| title_short | Accuracy and Usability of Smartphone-Based Distance Estimation Approaches for Visual Assistive Technology Development |
| title_sort | accuracy and usability of smartphone based distance estimation approaches for visual assistive technology development |
| topic | Assistive technology sensory substitution blindness low vision navigation |
| url | https://ieeexplore.ieee.org/document/10414161/ |
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